Pharma Tech Outlook: Pharma Tech Magazine


Pharma Tech Outlook | Monday, November 30, 2020

FREMONT, CA: Multiple aspects of human life are determined by an individual’s genetics. Better understandings of genetic makeup can assist scientists to comprehend, predict, and change the function of genes. The world of genomics has made significant strides in the past several years. According to the latest report, artificial intelligence (AI) systemswill be the next big players in both global healthcare and genomics. By 2021, AI will be responsible for 6.7 billion dollars in revenue, predicts the report. When researchers can sequence and analyze DNA, something that AI systems make faster, cheaper, and more accurate, they gain improved efficiency. Read on to know more.

The ability to sequence DNA offers researchers with the provision to read the genetic blueprint that directs all the activities of a living creature. Researchers today are using AI to identify patterns within high volume genetic data sets. These patterns are then transformed to computer models, which may help predict the probability of developing certain diseases or help inform the design of potential therapies. Researchers are also using machine learning to go deep in the interpretation of genetic information like the impact of individual genes.

Check This Out: Genomics Solutions Companies

Present applications of AI in the field of genomics are impacting how genetic research is conducted, how clinicians offer patient care, and make genomics more accessible to individuals interested in learning about how their heredity may impact their health. Firms use AI to help researchers interpret genetic variation. Algorithms are developed based on patterns identified in large genetic data, which are then translated to computer models to help researchers interpret how genetic variation impacts key cellular processes. There are often gaps in the patient data available to the healthcare team serving a patient. This challenge has ignited an interest in leveraging AI to improve the efficiency of the clinical workflow process. The workflow model developed using AI will ultimately improve data accessibility.

Efforts to implement AI to help accelerate genomics is smart business. These efforts may also prove profitable for firms that are able to deliver tangible and sustainable solutions to the challenges in healthcare delivery. 

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